This sponsored post is produced by Looker.
Why is understanding your customers so difficult?
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When it comes to building a comprehensive view of customer health, more data is definitely better. Transactional data, data from internal sources, and data from third-party applications (such as Salesforce, Zendesk, and Marketo) are all critical to gaining a comprehensive view of your customers.
Unfortunately, even when a company does collect pertinent data, existing customer success tools confine users to inflexible, pre-baked customer health metrics. Since each company is inherently different, canned metrics rarely reflect true customer engagement and health.
Constructing a successful customer success management strategy — an intuitive, flexible solution that provides a 360-degree view of the customer experience quickly and simply, adapting seamlessly to the unique demands not just of each company but of each user — is a perfect example of “easier said than done.”
However, by boiling this strategy down to its three core components, it’s far easier to make the “said” truly “done”. Here’s how:
1. Centralize data
To create an end-to-end, holistic view of your customers, you need a centralized data warehouse that draws from multiple sources. Begin with a foundation of product usage data, then link it to your other customer data. Feature usage, user adoption, user growth, and other relevant health metrics reveal user engagement in real time. Build on that usage data, incorporating other data sources to round out the picture. Include Salesforce and other CRM records, along with data on the tickets created by your support system, which are invaluable for tracking the type and severity of issues customers encounter. Finally, branch out to “softer” qualitative data, such as a subjective “customer evangelism” score.
A successful solution leverages powerful computing to maximize speed and simplicity while eliminating manual reconciliation. A centralized view of all touchpoints and data collected for each customer is meaningful in contributing to a customized, aggregated customer health score.
2. Customize analyses
When it comes to customer health scoring, one size does not fit all. Determining what makes a customer relationship healthy—or not—is different for every business. At a hair salon, measuring monthly active users might be too ambitious. Slack measures concurrent users. Google focuses on making sure their content is sending their users to the right place, so they measure bounce back rates. Upworthy wants engaged users, so they look at a blend of total time on site and percent of total site content viewed, a metric they call “Attention Minutes”.
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Arrays of unique factors help define a meaningful customer health score. Standard, check-the-box metrics aren’t customized to the degree of granularity necessary to understand your customer’s interaction with your product. Yet many companies choose to use these metrics, often due to the limitations of their analytics tools. An instantly customizable solution transcends these weaknesses, allowing you to retain at-risk customers and expand accounts that are already showing success. The health score sits at the heart of both.
The best companies know that it’s never as simple as counting active users—you need to ask deeper questions. Is activity growing? Are users taking advantage of your most important features? Are support requests coming in (we’ve actually found them to be a positive sign!)? Are your customers taking advantage of all the user seats they are paying for? Custom tuning of scores can work magic for refocusing a team on something like growth or penetration of a new feature.
The health scoring process helps companies refocus their services on pushing customers toward features and best practices that encourage long-term success. This ultimately creates much stronger internal alignment about measuring and retaining happiness. In general, what you measure is what teams will optimize for.
3. Bridge analyses and action
How does an effective solution translate analysis into business value? How does it improve customer health and increase retention? The key is turning data into action.
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A well-designed customer success management strategy helps you meet the needs of accounts on every part of the spectrum: from entirely satisfied customer evangelists to those threatening to churn in favor of a competitor.
For unhappy customers, it’s about finding them early, understanding their pain points, and proactively making them successful. For the most happy customers, its about identifying the practices that drive their success, and understanding how to leverage those practices with other customers to drive further adoption and increase user engagement. You can focus on specific indicators such as “sticky” feature usage, in conjunction with broad indicators, such as overall company adoption and positive feedback.
A well-designed strategy is executed with the proper data infrastructure, and tools that can deliver data into everyday workflows and tools (e.g. embedding data in Salesforce or integrating data querying capabilities into Slack, etc.). This enables decision-makers across your organization to easily access and understand how each and every customer is doing. Sales and marketing can explore healthy customers by vertical, usage, and any other imaginable attribute to understand areas of success. Product and engineering can employ the score to refine products and drive customers toward “sticky” features. The executive team can draw on it to drive near-term decision-making and long-term strategy.
Looking forward
The three crucial features of a customer success management strategy are centralization, customization, and bridging the gap between analysis and action. We hope that this overview gets you thinking about what your healthy customers look like and how to identify them. Once that thinking has been done, building an effective scoring system is a simple process, and workflow integration is a logical next step.
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Dig deeper: If you’re beginning this process, check out some examples of companies already successfully conducting their customer success management.
Colin Zima is Chief Analytics Officer at Looker.
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